System for processing well log data

ABSTRACT

In a preferred embodiment the invention comprises a method of processing well log data which includes evaluating the said well log data to identify variations in the well log data which are indicative of thin beds of a selected thickness, and reducing the magnitude in the well log data of the identified variations by a magnitude related to the selected thickness.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention is related to processing well log data. More specificallythe invention is related to a system for improving the correlation ofwell log data to seismic data.

2. Background of the Invention

To properly interpret seismic data it is important to establish acorrespondence between the seismic data, which is recorded as a functionof time, and velocity and density logs, which are recorded as a functionof depth. Establishing this correspondence can be difficult, however,and a principal reason for this difficulty is that the velocity anddensity logs are responsive to variations in the subsurface which theseismic signal is unable to resolve, or to even detect.

Normally if seismic data and well log data are both available from asubsurface region of interest, the well log data are used in conjunctionwith the seismic data to locate a given bed in two-way travel time inorder to map the subsurface. Actual velocity, density or impedancevariations through the strata of the earth's subsurface can bedetermined from velocity and density log data. Forward modeling, basedon the measured velocity and/or density logs, creates a syntheticseismic trace which is then compared with measured or recorded surfaceseismic signals from the region near the wellbore from which the logdata were obtained. The process of tying synthetic traces derived fromlog data to seismic travel time is called calibration.

Velocity logs are used frequently in the geophysical industry toidentify key reflection events, extract seismic wavelets, assist in theconstruction of velocity macro-models and as a source of rock propertyinformation for seismic modeling and reservoir characterization.Traditionally, proper matching of velocity and density log depths toseismic trace time is an important element of seismic interpretation,but today practitioners are also frequently called upon to determine theeffects, on seismic data, of changes in the velocity and density due tochanges in hydrocarbons, porosity or lithology. However, these changeswhich may occur in the real earth may or may not be resolvable, or evendetectable, by the seismic data. Further, velocity and density logsoften are very complicated, with many severe oscillations which mayinhibit the interpreter's ability to determine what effect, if any, asingle oscillation or a series of oscillations on a log will have on theactual seismic data. To make effective use of the correlations ofseismic data with the well log data, a proper correlation needs to beestablished between the depth scale on the log data and the time scaleon the seismic data, and a method is needed for determining whichvariations in the log will have corresponding noticeable changes in theseismic data.

Velocity logs are generated by a downhole tool (sonde) which typicallyis lowered into a wellbore to a selected depth and as the tool is thenraised toward the surface, an acoustic signal is generated at atransmitting location on the logging tool, and detected at one or morereceiving locations on the logging tool. Because the distance betweenthe transmitting location and the receiver locations, as well as betweenthe two receiving locations is known, by measuring the differentialtravel time of the transmitted signal, the velocity of the subsurfaceinterval (either the compressional wave velocity or the shear wavevelocity, as the case may be) between the receivers, may be determined.The frequency of the transmitted acoustic signal is typically about10,000 Hz., and velocity measurements are made at intervals as small as10 centimeters (3.937 inches).

Similarly, density is measured by a downhole tool (sonde) which emitsgamma rays from a source and the returning gamma rays are detected bytwo gamma ray detectors. Dense formations absorb many gamma rays andreturn few, while lighter formations absorb fewer gamma rays and returnmore. If the tool is properly calibrated, a direct measurement ofdensity can be obtained. Density measurements may be made at intervalsas small as 10 centimeters.

Acoustic impedance is the product of density and compressional wavevelocity, and may be determined from compressional wave velocity log anddensity log, measurements. Elastic impedance is the product of densityand shear wave velocity, and may be determined from shear wave velocitylog and density log measurements.

In contrast to well log measurements, a seismic signal is generated byinjecting an acoustic signal from the earth's surface, which thentravels downwardly into the earth's subsurface. When the seismic signalencounters an interface between two subsurface strata having differentimpedances, a portion of the acoustic signal is reflected back to theearth's surface, where the reflected energy is detected by a sensor.Because high frequency signals cannot penetrate the earth's subsurfaceto the depths of interest in many hydrocarbon exploration prospects, themaximum frequency of the detected seismic signal will typically be about60 Hz, which means the bandwidth of the seismic data is several ordersof magnitude less than the bandwidth of the recorded velocity or densitylog. Accordingly, the bandwidth of the downgoing seismic wavelet doesnot enable the seismic signal to resolve the very thin beds recorded bythe velocity and density logs, and in many cases is scarcely able toeven detect these thin beds.

Resolution and detection of the seismic method is discussed in anarticle by R. S. Kallweit and L. C. Wood, The limits of resolution ofzero-phase wavelets, July 1982, Geophysics, Vol. 47, No. 7, pp1035-1046. This article shows that the composite seismic response of athin bed is partially annihilated by the reflection seismic method. Thisreduction in the returned reflection signal is due to the summation oftwo returning wavelets, resulting from reflections from the top andbottom of a single layer, that arrive at virtually the same time butwith opposite polarity. For very thin beds, the time delay between thereflection from the top of the layer and the reflection from the bottomof the bed is very small, and the attenuation is nearly complete. As thethickness of the bed increases, however, the reflected signal is onlypartially attenuated. FIG. 1 shows the amplitude of the thin bedreflection signal normalized to the amplitude of the reflection signalthat would be returned from a thick bed reflection interface. Thisnormalized amplitude plot is referred to herein as the “tuning curve”.The two-way travel time between the bottom and top of the thin bed layeris plotted across the abscissa of FIG. 1. As the separation between thetop and bottom of the layer increases, the attenuation is lessened,until, at a specific separation, there is no reduction in signalamplitude, i.e., the tuning weight is equal to 1 (one). By “tuningweight” is meant maximum weight, at a given separation, of a compositewaveform created when a unit amplitude zero-phase wavelet is convolvedwith a unit amplitude dipole (i.e., +1, −1). As the separation betweenthe layers increases further, the amplitude actually increases until itreaches a maximum amplitude. At the time distance on this “tuning curve”where the maximum amplitude occurs, which is designated in FIG. 1 as“T_(R)”, the signal reflections from the top of the layer and from thebottom of the layer become separated, and reflections from the top andbottom of the layer will appear separately in a recorded seismic signal.This time distance, T_(R), which is referred to herein as the resolutionlimit, is typically about 10 milliseconds. For a layer 10 feet thick,with a velocity of 10,000 feet per second, the two way travel time is 2milliseconds, which is well below the resolution limit, T_(R),therefore, the seismic response of this layer will be greatly reduced.From this illustration, it is clear that the seismic signal may begreatly attenuated, and that the recorded seismic signal will not beable to resolve the signal returned from a layer through which the twoway travel time (TWTT) of the seismic signal is less than T_(R).

In order to aid the practitioner in correlating the velocity and densitylogs with seismic data, methods have been utilized in the prior art toremove the high frequency portion of these logs. These prior arttechniques are based on filtering of the log data. For example, a lowpass filter has often been applied to the velocity or density logs.However, this approach removes jumps in the log data and it mayintroduce artifacts whenever velocity spikes occur on the log. Ratherthan removing the thin bed spikes, this method merely smooths the logdata, so that error is introduced in adjacent locations and importantjumps may be eliminated.

In another prior art filtering method, the median filter method, amoving window is applied to the log and the center value within thismoving window is replaced with the median value within the window. Thismethod will replace high frequency spikes with reasonable values and hasthe advantage of preserving jumps in the sonic log. Nevertheless, thistechnique employs no guiding principles on the correct amount of eachspike and/or jump to preserve and, conversely on the correct amount toremove.

There remains a long felt need in the industry for an improved methodfor processing log data to assist the explorationist in correlating thelog data with seismic data. It is an object of this invention to providesuch an improved method.

SUMMARY OF THE INVENTION

In a preferred embodiment the invention comprises a method of processingwell log data which includes evaluating the said well log data toidentify variations in the well log data which are indicative of thinbeds of a selected thickness, and reducing the magnitude in the well logdata of the identified variations by a magnitude related to the selectedthickness.

In another embodiment the invention comprises a method of processingwell log data which includes generating a reflection coefficient seriesfrom either compressional wave velocity log data, sonic wave velocitydata, density log data, acoustic impedance log data or elastic impedancelog data and locating in the reflection coefficient series pairs ofreflection coefficients of opposite polarity and with the time spacingbetween the two reflection coefficients which is within the thicknessrange of a thin bed. For each said pair of reflection coefficients, themagnitude of the reflection coefficient having the smaller magnitude isdetermined and this smaller magnitude is subtracted from the magnitudeof each reflection coefficient of the pair, thereby developing a firstmodified reflection coefficient series. For each pair of reflectioncoefficients, the smaller magnitude is then multiplied by a factor whichis related to the time spacing in the log data between the pair ofreflection coefficients, and the resulting multiplied magnitude isstored in a data storage array at a location corresponding to thelocations of the pair of reflection coefficients to develop a secondmodified coefficient series. The first and second modified reflectioncoefficient series are then summed and the resulting summed coefficientseries are inverted to generate a modified well log data of the typefrom which said reflection coefficient series was calculated.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention and its advantages will be more easily understood byreference to the following description and the attached drawings inwhich:

FIG. 1 shows the effect of a thin bed on the amplitude of a reflectedseismic signal.

FIG. 2 shows a typical compressional wave velocity well log and aseismic trace for the location of the wellbore in which thecompressional wave velocity log was measured.

FIG. 3 shows the steps of a particular implementation of the invention.

FIG. 4 shows the results of applying the invention to the compressionalwave velocity log of FIG. 2.

FIG. 5 shows an example of the second output of the invention, asapplied to the compressional wave velocity log of FIG. 2.

While the invention will be described in connection with its preferredembodiments, it will be understood that the invention is not limitedthereto, but shall include all alternatives, modifications, andequivalents within the scope of the appended claims.

DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 2 shows a typical compressional wave velocity well log designatedby numeral 30 recorded at wellbore depths extending from about 8225 feetto 9000 feet. This compressional wave velocity log shows the variationsin compressional wave velocity along the length of the wellbore. FIG. 2also shows a seismic trace designated by numeral 32 generated for thelocation of the wellbore in which the compressional wave velocity logwas measured. Perturbations in the seismic trace represent reflectionsfrom subsurface interfaces of a seismic signal generated at the surface.Although the compressional wave velocity and density well logs arerecorded as a function of depth and the seismic trace is recorded as afunction of time, the well logs and the seismic trace are shown inhorizontal alignment so that the perturbations in the seismic trace aresubstantially aligned with the log variations representing thesubsurface variations which produced the seismic signal perturbations.Although not shown in FIG. 2, a shear wave velocity log, a density log,an acoustic impedance log or an elastic impedance log would each exhibithigh frequency fluctuations similar to those exhibited by thecompressional wave velocity log.

The steps of a particular implementation of the invention are outlinedin FIG. 3. Step 1 is to calculate a reflection coefficient series basedon log data. Either the compressional wave velocity data, the shear wavevelocity data, the density data, the acoustic impedance data or theelastic impedance data may be utilized for calculating the reflectioncoefficient series utilized in performing the invention. Either ol fivecomputations may be made to develop this reflection coefficient series,depending on whether compressional wave velocity data, the shear wavevelocity data, the density data, the acoustic impedance data or theelastic impedance data are utilized.

If compressional wave velocity data or shear wave velocity data areutilized the following equation is utilized for computing the reflectioncoefficient series: $\begin{matrix}{\text{Reflection Coefficient} = {\frac{( {V_{2} - V_{1}} )}{( {V_{2} + V_{1}} )}.}} & \text{Eq.~~1}\end{matrix}$

If density data are utilized the following formula is used:$\begin{matrix}{{\text{Reflection Coefficient} = \frac{( {\rho_{2} - \rho_{1}} )}{( {\rho_{2} + \rho_{1}} )}},} & \text{Eq.~~2}\end{matrix}$

and if acoustic impedance data or elastic impedance data are utilizedthe following formula is used: $\begin{matrix}{{\text{Reflection Coefficient} = \frac{( {{\rho_{2}V_{2}} - {\rho_{1}V_{1}}} )}{( {{\rho_{2}V_{2}} + {\rho_{1}V_{1}}} )}},} & \text{Eq.~~3}\end{matrix}$

where:

V₂=velocity (either compressional wave or shear wave) of the layer belowthe reflecting interface

V₁=velocity (either compressional wave or shear wave) of the layer abovethe reflecting interface

ρ₂=density of the layer below the reflecting interface

ρ₁=density of the layer above the reflecting interface.

In each instance, the reflection coefficient is computed for adjacentpairs of log data samples. Reflection coefficients may be computed atthe same intervals as the log measurement intervals. Accordingly, for awell in which the log measurement interval is 10 centimeters (3.937inches), reflection coefficients may also be computed at 10 centimeterintervals. The calculated reflection coefficient series is stored in afirst data storage array, in positions corresponding to the locations ofthe calculated reflection coefficients in the well log. This reflectioncoefficient series may be referred to herein as the initial reflectioncoefficient series.

In step 2, the two way travel time of a compressional wave signal orshear wave signal between the location of each adjacent calculatedreflection coefficient is computed. If it is desired to correlate thewell log data with a compressional wave seismic trace, the compressionalwave travel time would be computed. If it is desired to correlate thewell log data with a shear wave seismic trace the shear wave travel timewould be computed. The distance between the locations of the calculatedadjacent reflection coefficients will be known from the log data. Thetravel time of the compressional or shear wave signal may then becomputed from the known distance and velocity data measured in thecompressional or shear wave velocity log according to formulae wellknown to those of ordinary skill in the art. Although the distancebetween locations of adjacent reflection coefficients will normally bethe same throughout the length of the well log, the two way travel timebetween these locations will vary because of velocity variations alongthe length of the wellbore.

In step 3 a tuning curve for a zero phase wavelet is created, in theform shown in FIG. 1, based on the frequency of the actual seismic data.Each amplitude on this curve represents the maximum amplitude of acomposite waveform created when a zero phase wavelet with the samebandwidth as the seismic data is convolved with a +1, −1 spike pair(called a dipole) at a certain time separation. The maximum amplitude ofthe seismic wavelet is also set to one. By systematically increasing thetime separation of the dipole pair and convolving with the normalizedwavelet and selecting the maximum amplitude of the composite for eachtime separation, a tuning curve can be generated for all separationsbelow T_(R). Note that some separations near T_(R) actually increase themaximum amplitude to a value greater than one. Because of the selectionof a unit dipole as reflection coefficient and a maximum amplitude ofone for the wavelet, this tuning curve can be used on any dipole pairregardless of amplitude by merely multiplying the dipole pair by itscorresponding value on the tuning curve. As used with reference to thisinvention, a “thin bed” is a subsurface layer having a time separationbetween the top and bottom of the layer less than the separationrequired for reflections from the top and bottom of the layer to appearseparately in a seismic record.

In step 4, the reflection coefficient series is searched for thin beds.Reflection coefficient pairs of opposite polarity indicate the presenceof a subsurface stratum whose upper and lower boundaries coincide withthe locations for which the reflection coefficients were calculated.Accordingly, the reflection coefficients are searched to identify allpairs of reflection coefficients having opposite polarity and a timespacing below resolution, T_(R), for the seismic data recorded at thewellbore location. Normally all reflection coefficients from adjacentpositions in the reflection coefficient series having opposite polaritywill have a time spacing below resolution for the seismic data.

In step 5. for each reflection coefficient pairs identified in step 4,the magnitude of the reflection coefficient having the smaller magnitudeis determined and this smaller magnitude is subtracted from themagnitude of each of the reflection coefficients of the reflectioncoefficient pair, so that the magnitude of the smaller of the tworeflection coefficients will be reduced to zero. The larger reflectioncoefficient will have a non-zero residual.

In step 6, the magnitude of the smaller of the two reflectioncoefficients is then multiplied by a “tuning weight”, as determined instep 3, and this weighted magnitude is stored in a second data storagearray in locations corresponding to the location in the well log forwhich the pair of reflection coefficients were initially computed. The“tuning weight” is based on the observation that a thin bed willgenerate only a single perturbation in a seismic signal. For thin bedswhich are thinner than the resolution thickness, the detected seismicsignal will include a skew-symmetric waveform and the maximum amplitudeof this waveform will diminish as the thickness of the bed diminishes.Accordingly, the spike pairs that are stored in the storage location aremultiplied by a factor equal to the precise value of the tuning curvecorresponding to the two way travel time between the two samples. Sincethe tuning curve generated in step is created by convolving a zero phasewavelet with a maximum amplitude of one with a unit amplitude dipolepair, the spike pairs can be multiplied from the log by the tuning curvebecause it has been normalized during its construction.

Steps 4, 5 and 6 are performed sequentially for each pair of adjacentreflection coefficients in the reflection coefficient series. Forreflection coefficients whose magnitudes have been attenuated by acomputation in step 5, when the reflection coefficient is subsequentlypaired with another reflection coefficient, the magnitude is maintainedat the attenuated level when the step 5 computation is repeated.

After steps 4, 5 and 6 have been performed for each adjacent pair ofreflection coefficients, the process of steps 4, 5 and 6 is repeated forpairs of reflection coefficients spaced apart by two reflectioncoefficient locations. Repetition of the process of steps 4, 5 and 6continues with the spacing between selected pairs of reflectioncoefficients being successively incremented by one, until no more pairsof reflection coefficients are found of opposite polarity for which thetime spacing between the samples is below the resolution limit, T_(R),for the seismic signal. The contribution of thin beds has now beendeleted from the residual reflection coefficient series remaining in thefirst data storage array, and the weighted magnitudes stored in thesecond data storage array have formed an auxiliary reflectioncoefficient series representing the contribution of the thin beds to aseismic signal generated near the wellbore.

In step 7, a first output of the invention is generated, in which theresidual reflection coefficient series remaining after the attenuationsresulting from the repetitions of steps 4, 5 and 6 is reconverted to afirst modified log, from which the contribution of the thin beds to thelog have been deleted. FIG. 4, which shows the results, designated bynumeral 34, of applying the invention to the compressional wave velocitylog shown in FIG. 2, represents this first output. Note the limitednumber of velocity jumps, in comparison to the velocity log ol FIG. 2.The original velocity log, designated by numeral 30 is overlain in FIG.4 for comparison.

In step 8, a second output of the invention is generated, in which theweighted auxiliary reflection coefficient series stored in the seconddata storage array is added to the residual reflection coefficientseries, and this summed reflection coefficient series is reconverted toa second modified log, the presence of the thin beds, as they wouldappear to a seismic signal can now be seen in this second modified log.Many of the thin beds are effectively removed. Some of the thicker bedsare merely reduced in importance but are still observable, but now therelative importance of the layering (to a seismic signal) is put on anequal basis.

An alternative method of performing step 8 is to regenerate an auxiliarylog from the weighted auxiliary reflection coefficient series stored inthe second data storage array, and then sum this auxiliary log with thefirst modified log generated in step 7.

FIG. 5 shows an example,designated by numeral 30, of the second outputof the invention, as applied to the compressional wave velocity logshown in FIG. 2, overlaid on the compressional wave velocity log shownin FIG. 2, and designated by numeral 36. The presence of the thin beds,as they would appear to a seismic signal can now be seen. Many of thethin beds are effectively removed. Some of the thicker beds are merelyreduced in importance but are still observable, but now the relativeimportance of the layering (to a seismic signal) is put on an equalbasis.

In performing the invention, “thin-bed” effects are removed from the log(either the compressional wave velocity, sonic wave velocity, density,acoustic impedance or elastic impedance log, as the case may be) in sucha way that abrupt velocity changes which are present in the subsurfaceare maintained in the log. The log does not suffer the amplitudedistortion which results from the prior art method of simply applying alow pass filter to the log data. In the preferred embodiment of theinvention described herein, only those samples which the seismic methodcould not detect are removed from the log data. The resulting processedlog is much simpler than the original log, but jumps in the log data arepreserved if the reflection from the jump is detectable by the seismictechnique. Matching of the log to the seismic data is facilitatedbecause strata which are meaningless to the seismic data are removed andlog variations in different strata have been given the value that wouldbe seen by the seismic signal.

It is important to recognize that an integrated log generated inaccordance with this invention should not be used to build a syntheticseismic data or to calculate travel times; but merely as an interpretivetool to address the relative importance, from an amplitude-based pointof view, of the interpretive significance of each layer. Note that therehas been no loss of information in the integrated log other than thatwhich the seismic data is unable to see. To the extent that a given bedis detectable, it is still represented.

Those of ordinary skill in the art will recognize that the steps of thisinvention will normally be implemented on a digital computer, and thatcomputer instructions readable by a digital computer and defining themethod of the invention will be stored on a storage medium such asmagnetic tape, a magnetic or optical disk or an equivalent storagedevice and will instruct the computer to perform the method.

It will be appreciated that various modifications and variations may bemade to the invention without departing from the scope of the inventionas defined in the appended claims. It is the intent to cover within thescope of the appended claims all such modifications and variations.

I claim:
 1. A method of processing well log data comprising: evaluatingsaid well log data to identify variations in said well log data whichare indicative of thin beds of a selected thickness; and reducing themagnitude in said well log data of said identified variations by amagnitude related to said selected thickness.
 2. The method of claim 1wherein said well log data are compressional wave velocity data.
 3. Themethod of claim 1 wherein said well log data are shear wave velocitydata.
 4. The method of claim 1 wherein said well log data are densitydata.
 5. The method of claim 1 wherein said well log data are acousticimpedance data.
 6. The method of claim 1 wherein said well log data areelastic impedance data.
 7. A method of processing well log datacomprising: locating in a reflection coefficient series calculated fromwell log data consisting of one of the following types: compressionalwave velocity log data, shear wave velocity data, density log data,acoustic impedance log data or elastic impedance log data, pairs ofreflection coefficients of opposite polarity and spaced apart within thethickness range of a thin bed; for each said pair of reflectioncoefficients, determining the magnitude of the reflection coefficienthaving the smaller magnitude and subtracting said smaller magnitude fromthe magnitude of each reflection coefficient of said pair, therebydeveloping a first modified reflection coefficient series; for each saidpair of reflection coefficients, multiplying said smaller magnitude by afactor which is related to the time spacing in said log data betweensaid pair of reflection coefficients; and storing the resultingmultiplied magnitude in a data storage array at a location correspondingto the locations of said pair of reflection coefficients, therebydeveloping a second modified reflection coefficient series; summing saidfirst modified reflection coefficient series and said second modifiedreflection coefficient series; and inverting said summed first andsecond coefficient series to generate modified well log data of the typefrom which said reflection coefficient series was calculated.
 8. Amethod of processing well log data comprising: generating an initialreflection coefficient series from well log data consisting of one ofthe following types: compressional wave velocity data, shear wavevelocity data, density log data, acoustic impedance log data or elasticimpedance log data; determining in said initial reflection coefficientseries pairs of reflection coefficients of opposite polarity and spacedapart within the thickness range of a thin bed; attenuating bothreflection coefficients of each said pair by a factor related to thespacing between said pair thereby generating a modified reflectioncoefficient series; and inverting said modified reflection coefficientseries to generate a modified well log data of the type from which saidinitial reflection coefficient series was calculated.
 9. A method ofprocessing well log data comprising generating an initial reflectioncoefficient series from well log data consisting of one of the followingtypes: compressional wave velocity data, shear wave velocity data,density log data, acoustic impedance log data or elastic impedance logdata; determining in said initial reflection coefficient series pairs ofreflection coefficients of opposite polarity and spaced apart within thethickness range of a thin bed; for each said pair of reflectioncoefficients, determining the magnitude of the reflection coefficienthaving the smaller magnitude and subtracting said smaller magnitude fromthe magnitude of each reflection coefficient of said pair, therebydeveloping a first modified reflection coefficient series; for each saidpair of reflection coefficients, multiplying said smaller magnitude by afactor which is related to the time spacing in said log data betweensaid pair of reflection coefficients; and storing the resultingmultiplied magnitude in a data storage array at a location correspondingto the locations of said pair of reflection coefficients, therebydeveloping a second modified reflection coefficient series; invertingsaid first modified reflection coefficient series to generate firstmodified well log data of the type from which said reflectioncoefficient series was calculated; summing said first modifiedreflection coefficient series and said second modified reflectioncoefficient series; and inventing said summed first and secondcoefficient series to generate second modified well log data of the typefrom which said reflection coefficient series was calculated.
 10. Adevice adapted for use by a digital computer wherein a plurality ofcomputer instructions readable by said digital computer are encoded,which instructions instruct the computer to perform a processcomprising: generating an initial reflection coefficient series fromwell log data consisting of one of the following types: compressionalwave velocity data, shear wave velocity data, density log data, acousticimpedance log data or elastic impedance log data; determining in saidinitial reflection coefficient series pairs of reflection coefficientsof opposite polarity and spaced apart within the thickness range of athin bed; for each said pair of reflection coefficients, determining themagnitude of the reflection coefficient having the smaller magnitude andsubtracting said smaller magnitude from the magnitude of each reflectioncoefficient of said pair, thereby developing a first modified reflectioncoefficient series; for each said pair of reflection coefficients,multiplying said smaller magnitude by a factor which is related to thetime spacing in said log data between said pair of reflectioncoefficients; and storing the resulting multiplied magnitude in a datastorage array at a location corresponding to the locations of said pairof reflection coefficients, thereby developing a second modifiedreflection coefficient series; inverting said first modified reflectioncoefficient series to generate first modified well log data of the typefrom which said reflection coefficient series was calculated; summingsaid first modified reflection coefficient series and said secondmodified reflection coefficient series; and inverting said summed firstand second coefficient series to generate second modified well log dataof the type from which said reflection coefficient series wascalculated.
 11. The device of claim 10 wherein said device is selectedfrom the group consisting of a magnetic tape, a magnetic disk, and anoptical disk.